Manager, Data Engineering

Principal Duties And Responsibilities

• Build, lead, and manage the Data Engineering team, driving rapid delivery of data solutions that enhance analytics and insights capabilities.
• Manage 3–5 individual contributors as well as contract and vendor resources.
• Collaborate closely with stakeholders across product, architecture, development, business intelligence, and executive teams.
• Make recommendations for enterprise-wide data, data onboarding, and self-service analytics roadmap and architecture.
• Design data pipelines and data models optimized for BigQuery performance, cost control, and reliability.
• Provide technical direction and solution guidance to ensure projects enable effective data availability and meet business requirements.
• Serve as an escalation point for issues or roadblocks impacting delivery timelines.
• Stay current on emerging trends and technologies in Data Warehousing and Analytics—particularly within retail.
• Deliver solutions in a fast-paced, dynamic, and agile environment.
• Initiate proof-of-concepts (POCs) and prototypes to validate recommendations and test new approaches.
• Act as the subject-matter expert on data acquisition, ingestion, and information delivery.
• Lead the creation of standards for data quality, lineage, governance, observability, and CI/CD processes across the data engineering organization.
• Collaborate with data product owners to define, prioritize, and execute the data engineering roadmap aligned with business objectives.
• Coach and mentor engineers, fostering a culture of technical excellence and continuous improvement.

Minimum Requirements/Qualifications

• Bachelor’s degree or higher.
• 5+ years of experience working with large-scale, enterprise data sets.
• 2+ years managing full-time employees, contract partners, or vendor resources.
• Strong curiosity and a passion for identifying new ways to leverage data to create business value.
• Proven experience delivering end-to-end data solutions, with emphasis on enabling self-service analytics across diverse user groups.
• Experience working with end users to gather requirements and translate them into technical solutions from concept through implementation.
• Self-starter capable of independently delivering outcomes with minimal oversight.
• Hands-on experience working with structured and unstructured data and modern data technologies—including GCP, BigQuery, Dataflow, Python, etc.
• Experience delivering data as a product.
• Retail, supply chain, or e-commerce experience is a plus but not required.